Homepage

transformers@5.6.0

Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

  • latest version

    5.8.0

  • first published

    9 years ago

  • latest version published

    23 hours ago

  • licenses detected

  • View transformers package health on Snyk  (opens in a new tab)
    • Go back to all versions of this package
    Report a new vulnerability Found a mistake?

    Direct Vulnerabilities

    Known vulnerabilities in the transformers package. This does not include vulnerabilities belonging to this package’s dependencies.

    Fix vulnerabilities automatically

    Snyk's AI Trust Platform automatically finds the best upgrade path and integrates with your development workflows. Secure your code at zero cost.

    Fix for free
    VulnerabilityVulnerable Version
    • H
    Arbitrary Code Injection

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Arbitrary Code Injection via the convert_config function. An attacker can execute arbitrary code by supplying a malicious checkpoint file that is processed without proper validation.

    Note:

    The report of this vulnerability was rejected by the package's maintainers. See the project's security policy for more information.

    How to fix Arbitrary Code Injection?

    There is no fixed version for transformers.

    [0,)
    • H
    Arbitrary Code Injection

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Arbitrary Code Injection via the convert_config function. An attacker can execute arbitrary code by supplying a malicious checkpoint file that is processed without proper validation.

    Note:

    The report of this vulnerability was rejected by the package's maintainers. See the project's security policy for more information.

    How to fix Arbitrary Code Injection?

    There is no fixed version for transformers.

    [0,)
    • H
    Deserialization of Untrusted Data

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the parsing process of model files. An attacker can execute arbitrary code in the context of the current user by tricking a user into opening a malicious file or visiting a malicious page that triggers deserialization of untrusted data.

    Note:

    The report of this vulnerability was rejected by the package's maintainers. See the project's security policy for more information.

    How to fix Deserialization of Untrusted Data?

    There is no fixed version for transformers.

    [0,)
    • H
    Deserialization of Untrusted Data

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the megatron_gpt2 process. An attacker can achieve arbitrary code execution by tricking a user into opening a malicious file or visiting a crafted page that triggers deserialization of untrusted data.

    Note:

    The report of this vulnerability was rejected by the package's maintainers for being out of scope for the bug bounty program. See the project's security policy for more information.

    How to fix Deserialization of Untrusted Data?

    There is no fixed version for transformers.

    [0,)
    • H
    Arbitrary Code Injection

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Arbitrary Code Injection via the convert_config function. An attacker can execute arbitrary code by supplying a crafted checkpoint file that is processed without proper validation.

    Note:

    The report of this vulnerability was rejected by the package's maintainers for being out of scope for the bug bounty program. See the project's security policy for more information.

    How to fix Arbitrary Code Injection?

    There is no fixed version for transformers.

    [0,)
    • H
    Deserialization of Untrusted Data

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the parsing of checkpoints. An attacker can achieve arbitrary code execution by tricking a user into opening a malicious checkpoint file.

    Note:

    The report of this vulnerability was rejected by the package's maintainers for being out of scope for the bug bounty program. See the project's security policy for more information.

    How to fix Deserialization of Untrusted Data?

    There is no fixed version for transformers.

    [0,)
    • H
    Deserialization of Untrusted Data

    transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the parsing of weights. An attacker can execute arbitrary code by tricking a user into visiting a malicious page or opening a malicious file that triggers deserialization of untrusted data.

    Note:

    The report of this vulnerability was rejected by the package's maintainers for being out of scope for the bug bounty program. See the project's security policy for more information.

    How to fix Deserialization of Untrusted Data?

    There is no fixed version for transformers.

    [0,)
    Go back to all versions of this package